Skip to content

COMP5300 - Computing for Health and Medicine; Spring 2022 Course Project

Notifications You must be signed in to change notification settings

degradification/cardiovascular-risk-prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 

Repository files navigation

cardiovascular-risk-prediction

COMP5300 - Computing for Health and Medicine Course Project

Spring 2022

Team Members: Mustapha Ayad, Krestina Beshara, Dalton Grady, Bibi Hajira Mahammada, Prism Prajapati

Task - To predict the presence or absence of cardiovascular disease (CVD) using the patient examination results. Using five different models

  • Logistic Regression
  • Naive Bayes Bernoulli
  • K-Nearest Neighbor
  • Random Forest
  • Neural Network

Credits for Dataset : Svetlana Ulianova

Credits for Code : RobinReni

In order to compile and run the code, make sure the cardio_train.csv is downloaded in a 'data' directory as the code. When running the Neural Network model, create a directory within your working directory named 'logs' so that the Neural Network model will output its logs to that folder. To run the rest of the notebook, just run each cell individually or all at once.

About

COMP5300 - Computing for Health and Medicine; Spring 2022 Course Project

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published